





"""simple docstring"""





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE__   =  get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
       from transformers.models.mbart.modeling_mbart import shift_tokens_right

SCREAMING_SNAKE_CASE__   =  250_004
SCREAMING_SNAKE_CASE__   =  250_020

@require_sentencepiece
@require_tokenizers
class 						lowercase   (   _UpperCAmelCase	,    unittest.TestCase   ):
      _SCREAMING_SNAKE_CASE							      = MBartTokenizer
      _SCREAMING_SNAKE_CASE							      = MBartTokenizerFast
      _SCREAMING_SNAKE_CASE							      = True
      _SCREAMING_SNAKE_CASE							      = True





      def        _snake_case     (			self					)						->	int:
            super().setUp()

            # We have a SentencePiece fixture for testing
            lowerCAmelCase    		=			MBartTokenizer(lowercase ,		keep_accents=lowercase					)
            tokenizer.save_pretrained(self.tmpdirname					)





      def        _snake_case     (			self					)						->	List[Any]:
            lowerCAmelCase    		=			MBartTokenizer(lowercase ,		keep_accents=lowercase					)

            lowerCAmelCase    		=			tokenizer.tokenize("""This is a test"""					)
            self.assertListEqual(lowercase ,		["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]					)

            self.assertListEqual(
                tokenizer.convert_tokens_to_ids(lowercase					) ,		[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]] ,		)

            lowerCAmelCase    		=			tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
            self.assertListEqual(
                lowercase ,		[
                    SPIECE_UNDERLINE + """I""",
                    SPIECE_UNDERLINE + """was""",
                    SPIECE_UNDERLINE + """b""",
                    """or""",
                    """n""",
                    SPIECE_UNDERLINE + """in""",
                    SPIECE_UNDERLINE + """""",
                    """9""",
                    """2""",
                    """0""",
                    """0""",
                    """0""",
                    """,""",
                    SPIECE_UNDERLINE + """and""",
                    SPIECE_UNDERLINE + """this""",
                    SPIECE_UNDERLINE + """is""",
                    SPIECE_UNDERLINE + """f""",
                    """al""",
                    """s""",
                    """é""",
                    """.""",
                ] ,		)
            lowerCAmelCase    		=			tokenizer.convert_tokens_to_ids(lowercase					)
            self.assertListEqual(
                lowercase ,		[
                    value + tokenizer.fairseq_offset
                    for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                    #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
                ] ,		)

            lowerCAmelCase    		=			tokenizer.convert_ids_to_tokens(lowercase					)
            self.assertListEqual(
                lowercase ,		[
                    SPIECE_UNDERLINE + """I""",
                    SPIECE_UNDERLINE + """was""",
                    SPIECE_UNDERLINE + """b""",
                    """or""",
                    """n""",
                    SPIECE_UNDERLINE + """in""",
                    SPIECE_UNDERLINE + """""",
                    """<unk>""",
                    """2""",
                    """0""",
                    """0""",
                    """0""",
                    """,""",
                    SPIECE_UNDERLINE + """and""",
                    SPIECE_UNDERLINE + """this""",
                    SPIECE_UNDERLINE + """is""",
                    SPIECE_UNDERLINE + """f""",
                    """al""",
                    """s""",
                    """<unk>""",
                    """.""",
                ] ,		)





      def        _snake_case     (			self					)						->	Optional[int]:
            if not self.test_slow_tokenizer:
                  # as we don't have a slow version, we can't compare the outputs between slow and fast versions
                  return

            lowerCAmelCase    		=			(self.rust_tokenizer_class, """hf-internal-testing/tiny-random-mbart""", {})
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                  with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'					):
                        lowerCAmelCase    		=			self.rust_tokenizer_class.from_pretrained(lowercase ,		**lowercase					)
                        lowerCAmelCase    		=			self.tokenizer_class.from_pretrained(lowercase ,		**lowercase					)

                        lowerCAmelCase    		=			tempfile.mkdtemp()

                        lowerCAmelCase    		=			tokenizer_r.save_pretrained(lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.save_pretrained(lowercase					)

                        # Checks it save with the same files + the tokenizer.json file for the fast one
                        self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files					)					)
                        lowerCAmelCase    		=			tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f					)
                        self.assertSequenceEqual(lowercase ,		lowercase					)

                        # Checks everything loads correctly in the same way
                        lowerCAmelCase    		=			tokenizer_r.from_pretrained(lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.from_pretrained(lowercase					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                              self.assertTrue(hasattr(lowercase ,		lowercase					)					)
                              # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                              # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                        shutil.rmtree(lowercase					)

                        # Save tokenizer rust, legacy_format=True
                        lowerCAmelCase    		=			tempfile.mkdtemp()

                        lowerCAmelCase    		=			tokenizer_r.save_pretrained(lowercase ,		legacy_format=lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.save_pretrained(lowercase					)

                        # Checks it save with the same files
                        self.assertSequenceEqual(lowercase ,		lowercase					)

                        # Checks everything loads correctly in the same way
                        lowerCAmelCase    		=			tokenizer_r.from_pretrained(lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.from_pretrained(lowercase					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                              self.assertTrue(hasattr(lowercase ,		lowercase					)					)

                        shutil.rmtree(lowercase					)

                        # Save tokenizer rust, legacy_format=False
                        lowerCAmelCase    		=			tempfile.mkdtemp()

                        lowerCAmelCase    		=			tokenizer_r.save_pretrained(lowercase ,		legacy_format=lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.save_pretrained(lowercase					)

                        # Checks it saved the tokenizer.json file
                        self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files					)					)

                        # Checks everything loads correctly in the same way
                        lowerCAmelCase    		=			tokenizer_r.from_pretrained(lowercase					)
                        lowerCAmelCase    		=			tokenizer_p.from_pretrained(lowercase					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                              self.assertTrue(hasattr(lowercase ,		lowercase					)					)

                        shutil.rmtree(lowercase					)







@require_torch
@require_sentencepiece
@require_tokenizers
class 						lowercase   (   unittest.TestCase   ):
      _SCREAMING_SNAKE_CASE							      = 'facebook/mbart-large-en-ro'
      _SCREAMING_SNAKE_CASE							      = [
          ' UN Chief Says There Is No Military Solution in Syria',
          ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
      ]
      _SCREAMING_SNAKE_CASE							      = [
          'Şeful ONU declară că nu există o soluţie militară în Siria',
          'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
          ' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'
          ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
      ]
      _SCREAMING_SNAKE_CASE							      = [8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2, EN_CODE]





      @classmethod
      def        _snake_case     (			cls					)						->	Tuple:
            lowerCAmelCase    		=			MBartTokenizer.from_pretrained(
                cls.checkpoint_name ,		src_lang="""en_XX""" ,		tgt_lang="""ro_RO"""					)
            lowerCAmelCase    		=			1
            return cls





      def        _snake_case     (			self					)						->	str:
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""] ,		250_001					)
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""] ,		250_004					)
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""] ,		250_020					)





      def        _snake_case     (			self					)						->	str:
            lowerCAmelCase    		=			self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
            self.assertListEqual(self.expected_src_tokens ,		lowercase					)





      def        _snake_case     (			self					)						->	Any:
            self.assertIn(lowercase ,		self.tokenizer.all_special_ids					)
            lowerCAmelCase    		=			[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
            lowerCAmelCase    		=			self.tokenizer.decode(lowercase ,		skip_special_tokens=lowercase					)
            lowerCAmelCase    		=			self.tokenizer.decode(generated_ids[1:] ,		skip_special_tokens=lowercase					)
            self.assertEqual(lowercase ,		lowercase					)
            self.assertNotIn(self.tokenizer.eos_token ,		lowercase					)





      def        _snake_case     (			self					)						->	Tuple:
            lowerCAmelCase    		=			["""this is gunna be a long sentence """ * 20]
            assert isinstance(src_text[0] ,		lowercase					)
            lowerCAmelCase    		=			10
            lowerCAmelCase    		=			self.tokenizer(lowercase ,		max_length=lowercase ,		truncation=lowercase					).input_ids[0]
            self.assertEqual(ids[-2] ,		2					)
            self.assertEqual(ids[-1] ,		lowercase					)
            self.assertEqual(len(lowercase					) ,		lowercase					)





      def        _snake_case     (			self					)						->	Tuple:
            self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]					) ,		[250_026, 250_001]					)





      def        _snake_case     (			self					)						->	Optional[Any]:
            lowerCAmelCase    		=			tempfile.mkdtemp()
            lowerCAmelCase    		=			self.tokenizer.fairseq_tokens_to_ids
            self.tokenizer.save_pretrained(lowercase					)
            lowerCAmelCase    		=			MBartTokenizer.from_pretrained(lowercase					)
            self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,		lowercase					)





      @require_torch
      def        _snake_case     (			self					)						->	Any:
            lowerCAmelCase    		=			self.tokenizer(self.src_text ,		text_target=self.tgt_text ,		padding=lowercase ,		return_tensors="""pt"""					)
            lowerCAmelCase    		=			shift_tokens_right(batch["""labels"""] ,		self.tokenizer.pad_token_id					)

            # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
            assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
            assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
            assert batch.decoder_input_ids[1][-1] == 2
            assert batch.labels[1][-2:].tolist() == [2, RO_CODE]





      @require_torch
      def        _snake_case     (			self					)						->	Dict:
            lowerCAmelCase    		=			self.tokenizer(
                self.src_text ,		text_target=self.tgt_text ,		padding=lowercase ,		truncation=lowercase ,		max_length=len(self.expected_src_tokens					) ,		return_tensors="""pt""" ,		)

            lowerCAmelCase    		=			shift_tokens_right(batch["""labels"""] ,		self.tokenizer.pad_token_id					)

            self.assertIsInstance(lowercase ,		lowercase					)

            self.assertEqual((2, 14) ,		batch.input_ids.shape					)
            self.assertEqual((2, 14) ,		batch.attention_mask.shape					)
            lowerCAmelCase    		=			batch.input_ids.tolist()[0]
            self.assertListEqual(self.expected_src_tokens ,		lowercase					)
            self.assertEqual(2 ,		batch.decoder_input_ids[0, -1]					)  # EOS
            # Test that special tokens are reset
            self.assertEqual(self.tokenizer.prefix_tokens ,		[]					)
            self.assertEqual(self.tokenizer.suffix_tokens ,		[self.tokenizer.eos_token_id, EN_CODE]					)





      def        _snake_case     (			self					)						->	str:
            lowerCAmelCase    		=			self.tokenizer(self.src_text ,		padding=lowercase ,		truncation=lowercase ,		max_length=3 ,		return_tensors="""pt"""					)
            lowerCAmelCase    		=			self.tokenizer(
                text_target=self.tgt_text ,		padding=lowercase ,		truncation=lowercase ,		max_length=10 ,		return_tensors="""pt"""					)
            lowerCAmelCase    		=			targets["""input_ids"""]
            lowerCAmelCase    		=			shift_tokens_right(lowercase ,		self.tokenizer.pad_token_id					)

            self.assertEqual(batch.input_ids.shape[1] ,		3					)
            self.assertEqual(batch.decoder_input_ids.shape[1] ,		10					)





      @require_torch
      def        _snake_case     (			self					)						->	Optional[Any]:
            lowerCAmelCase    		=			self.tokenizer._build_translation_inputs(
                """A test""" ,		return_tensors="""pt""" ,		src_lang="""en_XX""" ,		tgt_lang="""ar_AR"""					)

            self.assertEqual(
                nested_simplify(lowercase					) ,		{
                    # A, test, EOS, en_XX
                    """input_ids""": [[62, 3_034, 2, 250_004]],
                    """attention_mask""": [[1, 1, 1, 1]],
                    # ar_AR
                    """forced_bos_token_id""": 250_001,
                } ,		)













"""simple docstring"""





import unittest

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device


if is_torch_available():
       import torch

       from transformers import AutoModelForImageClassification

if is_vision_available():
       from transformers import AutoImageProcessor

@require_torch
@require_vision
class 						lowercase   (   unittest.TestCase   ):





      @slow
      def        _snake_case     (			self					)						->	Any:
            lowerCAmelCase    		=			AutoImageProcessor.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""					)
            lowerCAmelCase    		=			AutoModelForImageClassification.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""					)
            model.to(lowercase					)

            from datasets import load_dataset

            lowerCAmelCase    		=			load_dataset("""nielsr/rvlcdip-demo"""					)

            lowerCAmelCase    		=			dataset["""train"""][0]["""image"""].convert("""RGB"""					)

            lowerCAmelCase    		=			image_processor(lowercase ,		return_tensors="""pt"""					).to(lowercase					)

            # forward pass
            with torch.no_grad():
                  lowerCAmelCase    		=			model(**lowercase					)
                  lowerCAmelCase    		=			outputs.logits

            lowerCAmelCase    		=			torch.Size((1, 16)					)
            self.assertEqual(logits.shape ,		lowercase					)

            lowerCAmelCase    		=			torch.tensor(
                [-0.4_158, -0.4_092, -0.4_347] ,		device=lowercase ,		dtype=torch.float ,		)
            self.assertTrue(torch.allclose(logits[0, :3] ,		lowercase ,		atol=1e-4					)					)






